Searching “Inaffectively”: A Behavioral, Psychometric, and Electroencephalographic Investigation of Psychopathic Personality and Visual-Spatial Attention
Bibliographic record
Abstract
Psychopathic personality’s characterization by abnormal visual-spatial attention and emotional response during visual search was evaluated in 3 related empirical investigations. Study 1 examined whether psychopathy impacts event-related potential (ERP) measures of stimulus salience (Ppc), target selection (N2pc), distractor suppression (Pd), and working memory (CDA). Psychopathic impulsivity traits were positively correlated with heightened visual-cortex salience calculations for distractor stimuli, requiring subsequent spatial suppression of those items. However, psychopathy was unassociated with target selection ability. Study 2 assessed whether psychopathy alters ERP measures of emotional face target salience (Ppc), selection (N2pc), and working memory representation (CDA). Similar to the results observed with low-level feature targets in study 1, even when targets were defined by complex emotional categories psychopathy remained unassociated with selection. Instead, the condition was negatively correlated with the strength of emotional face representations in working memory. Finally, study 3 tested whether individual differences in psychopathy explain longstanding discrepancies in a behavioral measure of efficiency during search for emotional faces (search slope). Detection of emotional targets was inefficient for all participants, and this effect was not moderated by the presence of psychopathic traits. These results clarify several mechanisms underlying the attention and affect irregularities proposed in theoretical models of psychopathic personality. Rather than failure to detect information outside immediate focus, study 1 suggests external stimuli are hyper salient during pre-attentive scans, but are reflexively hyper suppressed. Studies 2 and 3 demonstrate emotional expression detection is unimpaired, but affective abnormalities occur later during evaluation. Notably, across all participants the emotional status of stimuli was best reflected at evaluative stages, not spatial reorienting stages. This is in line with guided search attention models, which posit that only select low-level stimulus features have the capacity to direct visual-spatial focus, and psychological construction affect models, which argue that perception of discrete emotional states occurs during conceptual evaluation of ostensibly emotional objects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".